When people think about AI, what comes to mind tends to be the high-profile example of the Tesla car, virtual helpers like Alexa, or humanoid robots like Pepper. But we all know that AI technology goes far deeper and wider. For example, it’s enabling data-driven marketing teams to supercharge their performance, processes, decision-making and forecasting, and drive business innovation. And that’s happening today.
The technology does this by solving the thorny issue of disconnected data. It’s a problem when different marketing teams are working in the same building, but can get even worse in times like these, with mass homeworking.
So, many marketers find themselves working in data silos, even if that wasn’t the intention at the start. Stop me if this sounds familiar. Marketers have their own data sources; sales have theirs and client success teams have their own customer logs and metrics.
The problem is, there’s a lack of unifying infrastructure, which means teams are likely duplicating effort, using old or inaccurate data, and missing valuable customer and business insights. And it takes a huge cultural push to acquire the right tools or talent to break down the silos, so many firms carry on as usual.
Businesses that work in this disconnected, non-data-centric, way are lagging behind those that do, and that’s a bad thing. They’re missing out on opportunities and revenues, process efficiencies, customer experience improvements and sales. Meanwhile, rivals are racing ahead.
There’s an urgent need to stay competitive and adopt a system that can connect different data sources and data types together. One that will unite systems such as CRM, ad platforms, social media, e-commerce, customer service and sales databases. Then, the business can fully exploit its data and race ahead of the pack.
So, how do you go from data silos to data-driven? And is it even possible to integrate all your various sources of data to get greater insight and a holistic view of business performance — and do it in a straightforward and cost-effective way?
The answer lies in building a strong, unified data stack, one that can make a positive impact on business profitability. The big advantage for marketers is they can use it to drive business innovation through analytics.
Three steps to success
The SaaS business landscape is becoming increasingly competitive. Marketers often find themselves shouldering the weight of attracting and retaining customers, and increasing revenues. This makes the marketing team vitally important and puts them in a position to help the business grow and transform.
They can do this by being instrumental in establishing a data-driven culture. One where different departmental teams share information and collaborate to produce valuable new insights. Here’s how you can take the lead on becoming more insight and data-driven and set up a strong data stack that can improve business performance and profitability.
Step one: Business buy-in
Get stakeholders across the business on board with the data-driven vision, especially the commercial teams including marketing, business development, sales and client success. Everyone needs to recognize the value of sharing accurate, up-to-date information, accessing it from a central, unified repository, creating value from it, and making data-driven decisions.
Step two: Data integration and transformation
Find the right technology solution to build your marketing data stack. There are powerful tools and technologies available that will do the heavy lifting when it comes to ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). The right solution will automate back-end processes, integrate real-time data from hundreds of sources, and clean, organize and unify it, so it can be turned into actionable insights.
Step Three: Data visualization and augmented analytics
Data visualization enables marketers to create interactive dashboards that display data as metrics and KPIs through charts and graphs. This allows them to investigate and explore different data, alongside each other, to proactively discover trends, patterns, anomalies and opportunities through the use of AI, and specifically augmented analytics.
Augmented analytics in action
So, for example, using augmented analytics, businesses can apply predictive forecasting to optimize their budgets. It can also help them to act quickly on failing marketing or ad campaigns and revenue opportunities. Or they can carry out sophisticated customer segment analysis to target prospects and customers more effectively.
And by automating data science, augmented analytics gives marketers the tools they need to deliver strategic business insights. Marketing professionals can thereby offer an unbiased, neutral view of business data and channels through capabilities such as anomaly and trend detection, segment analysis, and forecasting.
Data-driven insights and decision-making should be the aim of all businesses, particularly SaaS and tech firms who are, by nature, focused on data. A data-driven culture among marketing teams opens the door to AI-enabled analytics. And this, in turn, empowers marketers to transform their own department and impact the business as a whole. As a result, marketers get to boost their productivity and acceleration and drive the customer experience, while also introducing efficiencies and innovation across the business.